There is now a great wealth of data available from neuroscientific studies of the human brain. "Neuroinformatics" is the new term used to encompass any combination of neuroscientific data and visualization, modeling and computational tools needed to understand this data. There are many challenges and opportunities to assist in processing and modeling this data. Magnetic resonance imaging (MRI) scans have inhomogeneities which need to be removed; undesired regions such as the skull need to be removed from the scans; the scans need to be parcellated into anatomical regions; functional activation data needs to be analyzed; new models for visualizing and understanding this data need to be developed. In this presentation I will discuss some of the methods that I am using address some of these challenges. For example, the cortical surface of the brain is very convoluted and most of the functional processing of the brain occurs on the cortical surface. I will describe a novel computational and visualization technique that I am implementing which uses the mathematical theory of circle packings to "unfold" and flatten the cortical surface to create a flat map of the brain. These maps exhibit conformal behavior and can be displayed in the Euclidean and hyperbolic planes and on a sphere and will allow individual differences in functional activation to be more easily compared. I will demonstrate how these maps are being used to elucidate new information about the human brain. If time permits, I will also discuss results that use other methods to model the electrical activity of the brain and illustrate the mapping between the visual field and visual cortex when a stimulus is presented in various positions in the visual field.